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HKeyBio Providers In Focus
Responses for Pipeline Bio
Before founding HKeyBio in 2017, our CEO, Raymond Zhao, spent ten years at GSK's R&D centre, where he led nonclinical research focused on immunology and neuroscience drug development. Biotech drug development was expanding rapidly in 2017, and he saw an opportunity to bring that experience to teams developing new therapies.
The founding ambition was to make preclinical research a stronger basis for evaluating and selecting drug candidates, as well as supporting IND submissions. That meant establishing well-characterised animal models that could help sponsors understand a candidate's activity and decide which therapies to advance, with the aim of improving their prospects in clinical development.
That thinking is reflected in our name: the H stands for human, and Key represents a translational key connecting preclinical research with human medicine. Human relevance has guided the company from the beginning.
Our core team's experience in large pharmaceutical companies has given us a practical understanding of what sponsors need from a research partner. Raymond's work at GSK helped shape our view that a preclinical study should be designed around a development decision. Sponsors need well-designed studies, reliable results and clear communication, together with an explanation of what the findings mean for their candidate.
At HKeyBio, we work closely with sponsors to understand their drug's mechanism of action, the disease biology and the specific research objective. That discussion shapes the model, treatment schedule and measurements. We also want clients to feel comfortable discussing unexpected findings with us, because working through those findings is an important part of a scientific partnership.
Autoimmune and allergic diseases share immune pathways, but the same pathway can behave differently across organs and disease stages. Staying focused allows us to build experience in those differences and apply it to each new project.
Over time, that focus has helped us develop disease models alongside pathology, immunophenotyping and biomarker assays. It also allows us to ask more specific questions: does a model contain the mechanism the drug is intended to change, and are we measuring that change in the relevant tissue?
Our purpose is to help sponsors evaluate and select therapies with a stronger scientific basis for clinical development. That means developing and choosing disease models that are relevant to the candidate's mechanism and the human disease processes being studied.
We connect in vivo pharmacology with biomarker assessment and scientific interpretation to understand whether a candidate acts on its intended pathway and changes disease-related outcomes. The evidence can support IND submissions while also helping sponsors decide which candidates to advance and what questions to address next. That is how we put our focus on human relevance into practice.
We start with the clinical problem and work back to an experiment that can address part of it. In inflammatory bowel disease, for example, a sponsor may want to understand whether a treatment improves epithelial barrier injury as well as reducing inflammation. That changes the choice of model, treatment window and tissue measurements.
The laboratory study can then examine drug exposure, pathway activity and intestinal pathology together. Those findings help the sponsor judge which effects to investigate further and which biomarkers might be useful clinically. As new patient data emerge, we can revisit the model and endpoints. That is how the two directions connect in practice.
The first conversation is about the question the sponsor needs to answer. We then examine how the therapy works, which disease processes matter, and whether a particular model contains those processes.
Two therapies for the same indication may need different models or study schedules. An antibody also needs to recognise and functionally modulate its target in the chosen species. We therefore consider target activity, exposure, disease stage and relevant endpoints before settling on a model. That makes the study more informative than selecting by disease name alone.
Good science means producing results that can be traced back to what was done and interpreted in the context of a clearly defined question.
In their first month, a new scientist would become familiar with our standard operating procedures, animal welfare requirements and study documentation. They would receive practical training under experienced colleagues and see how study directors and technical teams discuss experimental progress and unexpected findings.
We encourage people to ask why a measurement is being made, how it could be misleading, and what would be needed to support the conclusion. That habit matters as much as learning the technique.
Suzhou is our headquarters and a central base for scientific planning, laboratory work and project oversight. Our laboratory capabilities cover molecular and cell biology, pathology, small-animal research and bioanalysis. We also have NHP research operations in Suzhou and Guangxi, with the Nanning site supporting delivery of NHP disease-model studies.
For a client, the important point is that the study should work as one coordinated project. The protocol needs to connect the in vivo procedures with sample collection, laboratory analysis and reporting, with responsibilities agreed across the teams before work begins.
An NHP study can be valuable when the candidate's pharmacology or an important aspect of disease biology cannot be adequately examined in a rodent system. It can allow exposure, immune responses and tissue effects to be studied together in a species that is relevant to the particular therapy.
Species relevance has to be demonstrated for each candidate. An antibody's ability to bind a primate target does not by itself establish comparable functional activity, and some human therapeutics have limited activity in monkeys.
If a rodent model, a humanised mouse system or an in vitro assay can answer the question adequately, we would recommend that approach. An NHP study needs to add information that justifies its cost and animal use.
Our NHP omics database brings together RNA-seq and proteomics data across multiple immune-mediated disease models. RNA-seq provides a view of gene expression, while proteomics adds information about protein abundance. Together, they provide a molecular reference for understanding the biology represented in our models.
For a client, these data can help identify relevant pathways, select candidate biomarkers and assess which model is appropriate for the question they want to answer. They can also help interpret treatment-related changes alongside pathology and other study endpoints. Comparing the molecular features of a model with human disease data helps us understand both its relevance and its limitations.
Immune-cell-directed therapies have made the biggest difference to the questions we ask before an efficacy study. With a bispecific antibody or a T-cell engager, we need to consider the activity of each binding arm, the relevant cell populations and whether the model can support the intended interaction.
Degraders bring questions about intracellular target loss and how long it lasts. Antibody-drug conjugates require attention to target expression, internalisation and payload activity. Cell therapies add persistence, tissue distribution and changes in the host immune system.
These requirements determine the assays and sampling schedule. Our model portfolio provides options, but the choice still depends on the pharmacology of the individual candidate.
Our main contribution is disease-model selection and development, in vivo pharmacology, mechanism studies and translational biomarkers. Depending on the project, exposure measurements and immunogenicity assessment can help interpret the efficacy findings.
Clients bring in specialist partners for activities such as GLP toxicology, manufacturing, regulatory strategy and clinical development. These activities often need to be planned alongside pharmacology, so we aim to make our study design and reports useful to the wider development team. The relevant standards and deliverables should be clear for each work package.
One programme I would highlight involved a client developing an anti-fibrotic therapy. They initially approached us with liver fibrosis and idiopathic pulmonary fibrosis, or IPF, in mind.
Through scientific discussions, we suggested considering a broader range of diseases involving fibrosis. We introduced our seven families of fibrosis-related models as a framework for reviewing the options and helped the client broaden the study programme to additional disease settings.
The subsequent studies produced strong preclinical results in the additional indications evaluated. Those findings gave the client experimental support for a broader development strategy beyond the original liver fibrosis and IPF focus. It is a good example of how discussion about disease biology and model selection can expand the value of a research programme.
Yes. The anti-fibrotic programme is a good example. The client's starting point was liver fibrosis and IPF. Our discussions led us to recommend a wider range of fibrosis-related diseases and present our seven model families for consideration.
The client then explored additional indications, and the studies generated strong preclinical results in those broader disease settings. The discussion opened up the options; the experimental results provided support for pursuing them.
This is how we see indication expansion working in practice: identify plausible opportunities, select suitable models and generate evidence to assess them. For combination strategies, we would separately examine what each component contributes and whether the combination adds benefit under the study conditions.
An unexpected or weak response needs to be worked through carefully with the client. We would first review study conduct and the quality of the model and measurements. We would then examine whether the drug achieved sufficient exposure and whether there is evidence that it affected the intended pathway. For a biologic, anti-drug antibodies may also be relevant.
We discuss what the data support, what remains uncertain and which follow-up would best distinguish the possible explanations. The next step might be an additional assay or a revised sampling window rather than repeating the whole study. A well-designed negative study can still be useful if it helps the sponsor decide what to do next.
An NHP study needs a clear scientific justification. We consider whether the candidate has relevant pharmacological activity in the species, what the study can establish, and whether alternative methods can answer the question. The protocol also needs appropriate ethical review and a design that limits animal use and burden.
Our NHP work is conducted at AAALAC International-accredited facilities. That accreditation relates to the animal care and use programme, including veterinary care, housing, staff training and oversight. Day to day, the responsibilities include monitoring welfare, recognising concerns promptly and applying appropriate humane endpoints.
Traceability means being able to follow a reported result back through the analysis, sample and animal to the approved protocol and original record. The chain needs consistent identifiers, documented sample collection and handling, controlled procedures, and records of any changes or deviations.
Our quality management framework includes ISO 9001 certification. Before a report is issued, the checks need to connect the conclusions with the underlying records and ensure that departures from the protocol are accounted for. The practical value for the client is being able to understand how a result was generated and to resolve questions about it.
We address these points when defining the project, rather than leaving them until delivery. Confidentiality agreements and the study contract set out the handling of project information, rights to study data and intellectual property, and any permitted use of materials. Project access and data delivery arrangements should reflect those commitments.
For sample transfer, we agree what can be shipped, where it is going and what handling conditions are required. The route must be checked against the applicable permits, biosafety requirements and import and export rules. That planning is particularly important for international shipments and NHP-derived material.
They need experiments that can test a computational prediction and help prioritise candidates. That starts with confirming biological activity in a relevant assay and then choosing the next experiment according to the uncertainty that remains.
For immune therapies, we may need to examine pathway activity, immune-cell function or tissue responses before committing to a larger in vivo study. Clear assay conditions, suitable controls and well-organised data are valuable because they make results easier to compare and use in the next design cycle. Working with this approach puts greater emphasis on defining an informative experiment early.
The most useful role for AI in our work is as a support tool for literature review, organising scientific information and exploring complex datasets. It can help identify patterns or questions that deserve closer examination.
Scientists remain responsible for checking sources, judging biological relevance and deciding whether a result supports a conclusion. Animal study design and welfare decisions need that human responsibility. An AI-generated interpretation still has to be checked against the experimental records and underlying data, and client information has to be handled within the agreed confidentiality arrangements.
The 10–30% price reduction we announced for our NHP autoimmune disease-model services remains in effect, and we want more sponsors to know it is available.
We introduced this policy to help sponsors access important translational studies despite pressure on research budgets. A well-designed NHP study can provide valuable evidence for a development decision, and we want cost to be less of a barrier when that study is scientifically justified. We see this as an investment in long-term research partnerships.
Animal availability can still affect start dates. We therefore encourage sponsors to discuss their plans early, so we can review the animal requirements, screening needs and schedule alongside the study design. Sponsors can also contact us to discuss how the pricing policy applies to their proposed project.
These therapies require us to follow what happens to the immune system over time. For a B-cell-directed approach, blood depletion may be only one part of the picture. Tissue B cells, relevant antibody measures, immune recovery and disease-related organ changes may also matter.
For cell therapies, persistence and tissue distribution can be important; for T-cell engagers, target-dependent activity and cytokine responses need attention. Species compatibility has to be checked across the components required for the mechanism to work.
The follow-up should match the intended treatment effect. A short-term fall in a cell count cannot by itself establish durable disease control or restoration of immune tolerance.
The direction is towards choosing methods for the specific question they can answer. Human cell systems, ex vivo tissues and organ-on-chip approaches can provide useful mechanistic information and help prioritise candidates before an in vivo study.
I expect the next five years to bring closer integration of these methods with carefully justified animal work. Where systemic exposure, immune-cell trafficking or interactions between organs remain important uncertainties, an in vivo study may still contribute. Both animal and non-animal methods need evidence that they are suitable for their intended use.
Our aim is to build study programmes that use those strengths together and reduce animal work that does not add useful information.
We established HKeyBio Australia to work more closely with local biotech, pharmaceutical and research teams. Early discussions about a target or a study can be much more productive when there is a local scientific contact who understands the project and can stay involved as it develops.
For Australian teams, that means local scientific discussions and project coordination connected to our research capabilities in China. We want clients to be able to work through model selection, review emerging data and discuss the next step with someone who knows both their programme and the laboratory work.
Australia is an important option for teams considering early clinical development. From our perspective, the preclinical work is most useful when it is planned with the intended clinical questions in mind, including the mechanism, relevant exposure and biomarkers that may be carried forward.
We can contribute the pharmacology and translational evidence and discuss how it connects with the wider programme. First-in-human readiness also depends on the appropriate safety, manufacturing, regulatory and clinical work, coordinated with the relevant specialist partners.
I would like HKeyBio to be known for helping teams answer difficult questions in autoimmune and allergic disease development. That means having models whose strengths and limitations we understand, assays that explain a treatment response, and scientists who can work through uncertainty with a client.
Over the next five years, I would like us to strengthen the connections between human disease data, experimental models and new therapeutic modalities, while making that expertise easier for international teams to access.
Decide what result would change your next development decision before commissioning the study. That makes it much easier to choose the model, dose range, comparator and measurements, and to agree how both positive and negative findings will be interpreted.
Hidradenitis suppurativa. The disease can cause substantial pain and lasting tissue damage, and there is still a need to understand why patients respond differently to treatment. I would like to see therapies that bring sustained control and prevent progression, supported by better ways to identify which patients are likely to benefit.
Tissue-level pharmacodynamic measurements. A blood biomarker can be convenient, but a measurement in the affected tissue can help establish whether the drug reached the relevant compartment and changed the intended pathway. Paired with exposure and pathology, it can make a weak or unexpected efficacy result much easier to interpret.
The advice I would highlight is to be clear about what an experiment can establish. Before drawing a conclusion, I want to understand the controls, the quality of the measurements and the alternative explanations. That discipline helps us choose a useful next experiment and communicate honestly with the client.
